The applicant describes a 5-year career development program leading to independent academic research in biomedical networks under Marco Ramoni and co-mentors David Bates, Isaac Kohane, and Peter Szolovits. The applicant proposes a combined training and research program to lead to independence. Training involves biomedical methods underlying the networks being investigated by the applicant. On the research front, the hypothesis is that a holistic approach to the processing of information in biomedical networks is able to uncover novel types of relationships that could not be identified through current reductionistic methods. The aims are: 1) Design and develop a methodological framework, based on statistical signal processing, able to analyze biomedical networks and discover hidden relationships. 2) Develop and implement a scalable, modular architecture that is able to adaptively integrate information into the framework described in aim 1. 3) Apply the architecture in specific aim 2 to the development of a system for the analysis of large-scale EHR-based clinical informatics networks.